CBTI Summary
Consort map
Demographic information
Characteristic | N | Overall, N = 358 | control, N = 179 | treatment, N = 179 | p-value |
age | 358 | 36.34 ± 13.94 (18 - 73) | 35.95 ± 13.84 (18 - 73) | 36.72 ± 14.07 (18 - 71) | 0.599 |
gender | 358 | 0.792 | |||
female | 286 (80%) | 142 (79%) | 144 (80%) | ||
male | 72 (20%) | 37 (21%) | 35 (20%) | ||
occupation | 358 | 0.658 | |||
civil | 13 (3.6%) | 4 (2.2%) | 9 (5.0%) | ||
clerk | 57 (16%) | 30 (17%) | 27 (15%) | ||
craft | 12 (3.4%) | 8 (4.5%) | 4 (2.2%) | ||
homemaker | 26 (7.3%) | 14 (7.8%) | 12 (6.7%) | ||
manager | 28 (7.8%) | 16 (8.9%) | 12 (6.7%) | ||
other | 15 (4.2%) | 5 (2.8%) | 10 (5.6%) | ||
professional | 39 (11%) | 16 (8.9%) | 23 (13%) | ||
retired | 21 (5.9%) | 10 (5.6%) | 11 (6.1%) | ||
service | 12 (3.4%) | 7 (3.9%) | 5 (2.8%) | ||
student | 119 (33%) | 60 (34%) | 59 (33%) | ||
unemploy | 16 (4.5%) | 9 (5.0%) | 7 (3.9%) | ||
marital | 358 | 0.652 | |||
divorced | 14 (3.9%) | 5 (2.8%) | 9 (5.0%) | ||
married | 97 (27%) | 51 (28%) | 46 (26%) | ||
other | 2 (0.6%) | 1 (0.6%) | 1 (0.6%) | ||
separated | 5 (1.4%) | 1 (0.6%) | 4 (2.2%) | ||
single | 235 (66%) | 119 (66%) | 116 (65%) | ||
widowed | 5 (1.4%) | 2 (1.1%) | 3 (1.7%) | ||
education | 358 | 0.914 | |||
post-secondary | 52 (15%) | 28 (16%) | 24 (13%) | ||
primary | 2 (0.6%) | 1 (0.6%) | 1 (0.6%) | ||
secondary | 50 (14%) | 24 (13%) | 26 (15%) | ||
university | 254 (71%) | 126 (70%) | 128 (72%) | ||
family_income | 358 | 0.502 | |||
0_10000 | 56 (16%) | 27 (15%) | 29 (16%) | ||
10001_20000 | 75 (21%) | 38 (21%) | 37 (21%) | ||
20001_30000 | 73 (20%) | 42 (23%) | 31 (17%) | ||
30001_40000 | 60 (17%) | 31 (17%) | 29 (16%) | ||
40000_above | 94 (26%) | 41 (23%) | 53 (30%) | ||
religion | 358 | 0.110 | |||
buddhism | 16 (4.5%) | 7 (3.9%) | 9 (5.0%) | ||
catholic | 17 (4.7%) | 11 (6.1%) | 6 (3.4%) | ||
christianity | 73 (20%) | 30 (17%) | 43 (24%) | ||
nil | 248 (69%) | 130 (73%) | 118 (66%) | ||
other | 3 (0.8%) | 0 (0%) | 3 (1.7%) | ||
taoism | 1 (0.3%) | 1 (0.6%) | 0 (0%) | ||
source | 358 | 0.233 | |||
bokss | 15 (4.2%) | 11 (6.1%) | 4 (2.2%) | ||
131 (37%) | 63 (35%) | 68 (38%) | |||
12 (3.4%) | 7 (3.9%) | 5 (2.8%) | |||
other | 66 (18%) | 28 (16%) | 38 (21%) | ||
refresh | 134 (37%) | 70 (39%) | 64 (36%) | ||
1Mean ± SD (Range); n (%) | |||||
2Two Sample t-test; Pearson's Chi-squared test; Fisher's exact test | |||||
Measurement
Table
Characteristic | N | Overall, N = 358 | control, N = 179 | treatment, N = 179 | p-value |
isi | 358 | 13.47 ± 3.37 (8 - 21) | 13.53 ± 3.33 (8 - 21) | 13.40 ± 3.42 (8 - 21) | 0.719 |
who | 358 | 9.90 ± 3.74 (0 - 21) | 9.82 ± 3.71 (1 - 20) | 9.98 ± 3.77 (0 - 21) | 0.682 |
phq | 358 | 8.51 ± 5.01 (0 - 25) | 8.21 ± 4.98 (0 - 21) | 8.80 ± 5.03 (0 - 25) | 0.264 |
gad | 358 | 7.78 ± 5.12 (0 - 21) | 7.54 ± 5.03 (0 - 21) | 8.02 ± 5.21 (0 - 21) | 0.376 |
wsas | 358 | 16.73 ± 9.85 (0 - 40) | 16.77 ± 9.70 (0 - 39) | 16.69 ± 10.03 (0 - 40) | 0.936 |
shps_arousal | 358 | 3.10 ± 0.69 (1 - 5) | 3.02 ± 0.68 (1 - 5) | 3.18 ± 0.69 (1 - 5) | 0.025 |
shps_schedule | 358 | 3.55 ± 0.87 (1 - 6) | 3.53 ± 0.81 (2 - 6) | 3.58 ± 0.93 (1 - 6) | 0.653 |
shps_behavior | 358 | 2.05 ± 0.66 (1 - 4) | 1.99 ± 0.61 (1 - 4) | 2.12 ± 0.71 (1 - 4) | 0.059 |
shps_environment | 358 | 2.30 ± 0.82 (1 - 5) | 2.33 ± 0.84 (1 - 5) | 2.27 ± 0.80 (1 - 5) | 0.473 |
dbas_consequence | 358 | 6.61 ± 1.75 (1 - 10) | 6.59 ± 1.82 (1 - 10) | 6.64 ± 1.68 (1 - 10) | 0.772 |
dbas_worry | 358 | 14.37 ± 3.23 (3 - 20) | 14.20 ± 3.35 (3 - 20) | 14.54 ± 3.11 (3 - 20) | 0.319 |
dbas_expectation | 358 | 7.03 ± 2.14 (1 - 10) | 7.17 ± 2.09 (1 - 10) | 6.89 ± 2.19 (1 - 10) | 0.209 |
dbas_medication | 358 | 3.19 ± 2.07 (0 - 9) | 3.15 ± 2.04 (0 - 9) | 3.24 ± 2.09 (0 - 9) | 0.683 |
psas_somatic | 358 | 1.88 ± 0.69 (1 - 5) | 1.86 ± 0.66 (1 - 4) | 1.91 ± 0.71 (1 - 5) | 0.539 |
psas_cognitive | 358 | 2.92 ± 0.85 (1 - 5) | 2.87 ± 0.84 (1 - 5) | 2.97 ± 0.86 (1 - 5) | 0.270 |
psqi_global | 358 | 10.87 ± 3.02 (2 - 19) | 10.72 ± 3.03 (4 - 17) | 11.01 ± 3.00 (2 - 19) | 0.363 |
mic_attention | 358 | 1.36 ± 0.72 (0 - 3) | 1.30 ± 0.71 (0 - 3) | 1.42 ± 0.73 (0 - 3) | 0.110 |
mic_executive | 358 | 1.31 ± 0.76 (0 - 3) | 1.28 ± 0.77 (0 - 3) | 1.35 ± 0.76 (0 - 3) | 0.406 |
mic_memory | 358 | 1.37 ± 0.73 (0 - 3) | 1.33 ± 0.75 (0 - 3) | 1.40 ± 0.71 (0 - 3) | 0.397 |
nb_pcs | 358 | 46.27 ± 8.63 (17 - 65) | 46.33 ± 8.91 (17 - 63) | 46.20 ± 8.38 (21 - 65) | 0.879 |
nb_mcs | 358 | 39.94 ± 9.95 (8 - 65) | 39.90 ± 9.78 (8 - 62) | 39.98 ± 10.14 (8 - 65) | 0.935 |
1Mean ± SD (Range) | |||||
2Two Sample t-test | |||||
Plot
Data analysis
Table
Group | Characteristic | Beta | SE1 | 95% CI1 | p-value |
isi | (Intercept) | 13.5 | 0.286 | 13.0, 14.1 | |
group | |||||
control | — | — | — | ||
treatment | -0.128 | 0.404 | -0.921, 0.664 | 0.751 | |
time_point | |||||
1st | — | — | — | ||
2nd | -2.46 | 0.323 | -3.09, -1.82 | 0.000 | |
3rd | -2.85 | 0.333 | -3.50, -2.20 | 0.000 | |
group * time_point | |||||
treatment * 2nd | -2.96 | 0.487 | -3.92, -2.01 | 0.000 | |
treatment * 3rd | -2.99 | 0.497 | -3.96, -2.01 | 0.000 | |
Pseudo R square | 0.260 | ||||
who | (Intercept) | 9.82 | 0.305 | 9.22, 10.4 | |
group | |||||
control | — | — | — | ||
treatment | 0.162 | 0.432 | -0.685, 1.01 | 0.708 | |
time_point | |||||
1st | — | — | — | ||
2nd | 0.729 | 0.299 | 0.143, 1.32 | 0.015 | |
3rd | 0.919 | 0.308 | 0.315, 1.52 | 0.003 | |
group * time_point | |||||
treatment * 2nd | 1.40 | 0.453 | 0.513, 2.29 | 0.002 | |
treatment * 3rd | 1.64 | 0.463 | 0.731, 2.55 | 0.000 | |
Pseudo R square | 0.053 | ||||
phq | (Intercept) | 8.21 | 0.379 | 7.47, 8.95 | |
group | |||||
control | — | — | — | ||
treatment | 0.592 | 0.535 | -0.457, 1.64 | 0.269 | |
time_point | |||||
1st | — | — | — | ||
2nd | -0.779 | 0.333 | -1.43, -0.126 | 0.020 | |
3rd | -0.634 | 0.344 | -1.31, 0.040 | 0.066 | |
group * time_point | |||||
treatment * 2nd | -1.73 | 0.506 | -2.73, -0.742 | 0.001 | |
treatment * 3rd | -2.45 | 0.517 | -3.46, -1.44 | 0.000 | |
Pseudo R square | 0.039 | ||||
gad | (Intercept) | 7.54 | 0.382 | 6.79, 8.28 | |
group | |||||
control | — | — | — | ||
treatment | 0.480 | 0.540 | -0.578, 1.54 | 0.374 | |
time_point | |||||
1st | — | — | — | ||
2nd | -0.440 | 0.341 | -1.11, 0.229 | 0.198 | |
3rd | -0.595 | 0.352 | -1.28, 0.095 | 0.091 | |
group * time_point | |||||
treatment * 2nd | -2.07 | 0.518 | -3.09, -1.06 | 0.000 | |
treatment * 3rd | -2.37 | 0.529 | -3.41, -1.33 | 0.000 | |
Pseudo R square | 0.038 | ||||
wsas | (Intercept) | 16.8 | 0.749 | 15.3, 18.2 | |
group | |||||
control | — | — | — | ||
treatment | -0.084 | 1.059 | -2.16, 1.99 | 0.937 | |
time_point | |||||
1st | — | — | — | ||
2nd | -0.819 | 0.696 | -2.18, 0.544 | 0.239 | |
3rd | -0.089 | 0.717 | -1.49, 1.32 | 0.902 | |
group * time_point | |||||
treatment * 2nd | -2.95 | 1.055 | -5.02, -0.884 | 0.005 | |
treatment * 3rd | -4.95 | 1.078 | -7.06, -2.83 | 0.000 | |
Pseudo R square | 0.034 | ||||
shps_arousal | (Intercept) | 3.02 | 0.055 | 2.91, 3.13 | |
group | |||||
control | — | — | — | ||
treatment | 0.163 | 0.078 | 0.009, 0.316 | 0.039 | |
time_point | |||||
1st | — | — | — | ||
2nd | -0.196 | 0.059 | -0.312, -0.079 | 0.001 | |
3rd | -0.219 | 0.061 | -0.338, -0.099 | 0.000 | |
group * time_point | |||||
treatment * 2nd | -0.477 | 0.090 | -0.653, -0.302 | 0.000 | |
treatment * 3rd | -0.565 | 0.091 | -0.745, -0.386 | 0.000 | |
Pseudo R square | 0.112 | ||||
shps_schedule | (Intercept) | 3.53 | 0.067 | 3.40, 3.66 | |
group | |||||
control | — | — | — | ||
treatment | 0.042 | 0.094 | -0.143, 0.226 | 0.659 | |
time_point | |||||
1st | — | — | — | ||
2nd | -0.101 | 0.060 | -0.218, 0.017 | 0.094 | |
3rd | -0.132 | 0.062 | -0.253, -0.011 | 0.033 | |
group * time_point | |||||
treatment * 2nd | -0.345 | 0.091 | -0.523, -0.166 | 0.000 | |
treatment * 3rd | -0.425 | 0.093 | -0.607, -0.243 | 0.000 | |
Pseudo R square | 0.045 | ||||
shps_behavior | (Intercept) | 1.99 | 0.051 | 1.89, 2.08 | |
group | |||||
control | — | — | — | ||
treatment | 0.132 | 0.072 | -0.009, 0.273 | 0.067 | |
time_point | |||||
1st | — | — | — | ||
2nd | 0.024 | 0.051 | -0.075, 0.124 | 0.630 | |
3rd | 0.009 | 0.052 | -0.093, 0.112 | 0.860 | |
group * time_point | |||||
treatment * 2nd | -0.244 | 0.077 | -0.394, -0.094 | 0.002 | |
treatment * 3rd | -0.333 | 0.078 | -0.486, -0.179 | 0.000 | |
Pseudo R square | 0.020 | ||||
shps_environment | (Intercept) | 2.33 | 0.061 | 2.21, 2.45 | |
group | |||||
control | — | — | — | ||
treatment | -0.062 | 0.086 | -0.230, 0.106 | 0.469 | |
time_point | |||||
1st | — | — | — | ||
2nd | -0.058 | 0.060 | -0.176, 0.059 | 0.331 | |
3rd | -0.061 | 0.062 | -0.182, 0.060 | 0.323 | |
group * time_point | |||||
treatment * 2nd | -0.085 | 0.091 | -0.263, 0.092 | 0.347 | |
treatment * 3rd | -0.258 | 0.093 | -0.439, -0.076 | 0.006 | |
Pseudo R square | 0.021 | ||||
dbas_consequence | (Intercept) | 6.59 | 0.140 | 6.31, 6.86 | |
group | |||||
control | — | — | — | ||
treatment | 0.054 | 0.199 | -0.336, 0.443 | 0.787 | |
time_point | |||||
1st | — | — | — | ||
2nd | -0.336 | 0.141 | -0.612, -0.061 | 0.017 | |
3rd | -0.669 | 0.145 | -0.95, -0.385 | 0.000 | |
group * time_point | |||||
treatment * 2nd | -1.11 | 0.213 | -1.53, -0.693 | 0.000 | |
treatment * 3rd | -1.30 | 0.217 | -1.73, -0.873 | 0.000 | |
Pseudo R square | 0.117 | ||||
dbas_worry | (Intercept) | 14.2 | 0.284 | 13.6, 14.8 | |
group | |||||
control | — | — | — | ||
treatment | 0.341 | 0.401 | -0.445, 1.13 | 0.396 | |
time_point | |||||
1st | — | — | — | ||
2nd | -1.23 | 0.323 | -1.86, -0.598 | 0.000 | |
3rd | -1.84 | 0.333 | -2.50, -1.19 | 0.000 | |
group * time_point | |||||
treatment * 2nd | -2.71 | 0.487 | -3.67, -1.76 | 0.000 | |
treatment * 3rd | -2.87 | 0.497 | -3.84, -1.90 | 0.000 | |
Pseudo R square | 0.162 | ||||
dbas_expectation | (Intercept) | 7.17 | 0.172 | 6.84, 7.51 | |
group | |||||
control | — | — | — | ||
treatment | -0.285 | 0.244 | -0.763, 0.193 | 0.243 | |
time_point | |||||
1st | — | — | — | ||
2nd | -0.343 | 0.176 | -0.688, 0.002 | 0.052 | |
3rd | -0.772 | 0.181 | -1.13, -0.417 | 0.000 | |
group * time_point | |||||
treatment * 2nd | -1.25 | 0.266 | -1.77, -0.726 | 0.000 | |
treatment * 3rd | -1.28 | 0.272 | -1.82, -0.750 | 0.000 | |
Pseudo R square | 0.111 | ||||
dbas_medication | (Intercept) | 3.15 | 0.161 | 2.83, 3.46 | |
group | |||||
control | — | — | — | ||
treatment | 0.089 | 0.228 | -0.357, 0.536 | 0.695 | |
time_point | |||||
1st | — | — | — | ||
2nd | 0.366 | 0.164 | 0.044, 0.689 | 0.026 | |
3rd | 0.309 | 0.169 | -0.023, 0.642 | 0.068 | |
group * time_point | |||||
treatment * 2nd | -0.664 | 0.249 | -1.15, -0.176 | 0.008 | |
treatment * 3rd | -0.861 | 0.254 | -1.36, -0.363 | 0.001 | |
Pseudo R square | 0.015 | ||||
psas_somatic | (Intercept) | 1.86 | 0.051 | 1.76, 1.96 | |
group | |||||
control | — | — | — | ||
treatment | 0.045 | 0.072 | -0.096, 0.185 | 0.533 | |
time_point | |||||
1st | — | — | — | ||
2nd | 0.144 | 0.047 | 0.051, 0.236 | 0.003 | |
3rd | 0.006 | 0.049 | -0.090, 0.101 | 0.907 | |
group * time_point | |||||
treatment * 2nd | -0.306 | 0.072 | -0.447, -0.166 | 0.000 | |
treatment * 3rd | -0.238 | 0.073 | -0.381, -0.094 | 0.001 | |
Pseudo R square | 0.021 | ||||
psas_cognitive | (Intercept) | 2.87 | 0.063 | 2.75, 3.00 | |
group | |||||
control | — | — | — | ||
treatment | 0.099 | 0.090 | -0.077, 0.275 | 0.270 | |
time_point | |||||
1st | — | — | — | ||
2nd | -0.204 | 0.064 | -0.329, -0.079 | 0.001 | |
3rd | -0.363 | 0.066 | -0.492, -0.234 | 0.000 | |
group * time_point | |||||
treatment * 2nd | -0.434 | 0.097 | -0.623, -0.245 | 0.000 | |
treatment * 3rd | -0.407 | 0.099 | -0.600, -0.214 | 0.000 | |
Pseudo R square | 0.091 | ||||
psqi_global | (Intercept) | 10.7 | 0.237 | 10.3, 11.2 | |
group | |||||
control | — | — | — | ||
treatment | 0.291 | 0.335 | -0.367, 0.948 | 0.386 | |
time_point | |||||
1st | — | — | — | ||
2nd | -1.31 | 0.258 | -1.82, -0.807 | 0.000 | |
3rd | -1.31 | 0.266 | -1.84, -0.794 | 0.000 | |
group * time_point | |||||
treatment * 2nd | -1.86 | 0.389 | -2.62, -1.10 | 0.000 | |
treatment * 3rd | -2.44 | 0.398 | -3.22, -1.66 | 0.000 | |
Pseudo R square | 0.149 | ||||
mic_attention | (Intercept) | 1.30 | 0.057 | 1.19, 1.41 | |
group | |||||
control | — | — | — | ||
treatment | 0.122 | 0.080 | -0.035, 0.278 | 0.130 | |
time_point | |||||
1st | — | — | — | ||
2nd | -0.022 | 0.055 | -0.131, 0.087 | 0.694 | |
3rd | 0.034 | 0.057 | -0.079, 0.146 | 0.558 | |
group * time_point | |||||
treatment * 2nd | -0.248 | 0.084 | -0.412, -0.083 | 0.003 | |
treatment * 3rd | -0.387 | 0.086 | -0.555, -0.219 | 0.000 | |
Pseudo R square | 0.021 | ||||
mic_executive | (Intercept) | 1.28 | 0.058 | 1.17, 1.39 | |
group | |||||
control | — | — | — | ||
treatment | 0.067 | 0.082 | -0.094, 0.228 | 0.415 | |
time_point | |||||
1st | — | — | — | ||
2nd | -0.034 | 0.054 | -0.140, 0.073 | 0.538 | |
3rd | -0.051 | 0.056 | -0.161, 0.060 | 0.369 | |
group * time_point | |||||
treatment * 2nd | -0.159 | 0.083 | -0.321, 0.003 | 0.054 | |
treatment * 3rd | -0.270 | 0.084 | -0.435, -0.105 | 0.001 | |
Pseudo R square | 0.015 | ||||
mic_memory | (Intercept) | 1.33 | 0.057 | 1.22, 1.44 | |
group | |||||
control | — | — | — | ||
treatment | 0.066 | 0.081 | -0.093, 0.224 | 0.417 | |
time_point | |||||
1st | — | — | — | ||
2nd | 0.031 | 0.051 | -0.069, 0.132 | 0.538 | |
3rd | -0.065 | 0.053 | -0.168, 0.038 | 0.218 | |
group * time_point | |||||
treatment * 2nd | -0.276 | 0.078 | -0.428, -0.124 | 0.000 | |
treatment * 3rd | -0.218 | 0.079 | -0.373, -0.063 | 0.006 | |
Pseudo R square | 0.017 | ||||
nb_pcs | (Intercept) | 46.3 | 0.659 | 45.0, 47.6 | |
group | |||||
control | — | — | — | ||
treatment | -0.139 | 0.931 | -1.96, 1.69 | 0.882 | |
time_point | |||||
1st | — | — | — | ||
2nd | -0.871 | 0.591 | -2.03, 0.286 | 0.141 | |
3rd | -0.792 | 0.609 | -1.99, 0.402 | 0.194 | |
group * time_point | |||||
treatment * 2nd | 2.76 | 0.897 | 1.00, 4.52 | 0.002 | |
treatment * 3rd | 3.21 | 0.916 | 1.41, 5.00 | 0.000 | |
Pseudo R square | 0.016 | ||||
nb_mcs | (Intercept) | 39.9 | 0.771 | 38.4, 41.4 | |
group | |||||
control | — | — | — | ||
treatment | 0.085 | 1.090 | -2.05, 2.22 | 0.938 | |
time_point | |||||
1st | — | — | — | ||
2nd | 2.00 | 0.740 | 0.553, 3.45 | 0.007 | |
3rd | 2.26 | 0.763 | 0.764, 3.76 | 0.003 | |
group * time_point | |||||
treatment * 2nd | 3.57 | 1.122 | 1.37, 5.77 | 0.002 | |
treatment * 3rd | 4.67 | 1.146 | 2.43, 6.92 | 0.000 | |
Pseudo R square | 0.056 | ||||
1SE = Standard Error, CI = Confidence Interval | |||||
Text
isi
We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict isi with group and time_point (formula: isi ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.59) and the part related to the fixed effects alone (marginal R2) is of 0.26. The model’s intercept, corresponding to group = control and time_point = 1st , is at 13.53 (95% CI [12.97, 14.09], t(848) = 47.35, p < .001). Within this model:
- The effect of group [treatment] is statistically non-significant and negative (beta = -0.13, 95% CI [-0.92, 0.66], t(848) = -0.32, p = 0.751; Std. beta = -0.03, 95% CI [-0.21, 0.15])
- The effect of time point [2nd] is statistically significant and negative (beta = -2.46, 95% CI [-3.09, -1.82], t(848) = -7.61, p < .001; Std. beta = -0.55, 95% CI [-0.69, -0.41])
- The effect of time point [3rd] is statistically significant and negative (beta = -2.85, 95% CI [-3.50, -2.20], t(848) = -8.56, p < .001; Std. beta = -0.63, 95% CI [-0.78, -0.49])
- The interaction effect of time point [2nd] on group [treatment] is statistically significant and negative (beta = -2.96, 95% CI [-3.92, -2.01], t(848) = -6.09, p < .001; Std. beta = -0.66, 95% CI [-0.87, -0.45])
- The interaction effect of time point [3rd] on group [treatment] is statistically significant and negative (beta = -2.99, 95% CI [-3.96, -2.01], t(848) = -6.01, p < .001; Std. beta = -0.67, 95% CI [-0.88, -0.45])
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.
who
We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict who with group and time_point (formula: who ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.61) and the part related to the fixed effects alone (marginal R2) is of 0.05. The model’s intercept, corresponding to group = control and time_point = 1st , is at 9.82 (95% CI [9.22, 10.42], t(848) = 32.16, p < .001). Within this model:
- The effect of group [treatment] is statistically non-significant and positive (beta = 0.16, 95% CI [-0.68, 1.01], t(848) = 0.38, p = 0.708; Std. beta = 0.04, 95% CI [-0.16, 0.24])
- The effect of time point [2nd] is statistically significant and positive (beta = 0.73, 95% CI [0.14, 1.32], t(848) = 2.44, p = 0.015; Std. beta = 0.17, 95% CI [0.03, 0.31])
- The effect of time point [3rd] is statistically significant and positive (beta = 0.92, 95% CI [0.32, 1.52], t(848) = 2.98, p = 0.003; Std. beta = 0.22, 95% CI [0.07, 0.36])
- The interaction effect of time point [2nd] on group [treatment] is statistically significant and positive (beta = 1.40, 95% CI [0.51, 2.29], t(848) = 3.09, p = 0.002; Std. beta = 0.33, 95% CI [0.12, 0.54])
- The interaction effect of time point [3rd] on group [treatment] is statistically significant and positive (beta = 1.64, 95% CI [0.73, 2.55], t(848) = 3.54, p < .001; Std. beta = 0.39, 95% CI [0.17, 0.60])
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.
phq
We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict phq with group and time_point (formula: phq ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.68) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st , is at 8.21 (95% CI [7.47, 8.95], t(848) = 21.69, p < .001). Within this model:
- The effect of group [treatment] is statistically non-significant and positive (beta = 0.59, 95% CI [-0.46, 1.64], t(848) = 1.11, p = 0.269; Std. beta = 0.11, 95% CI [-0.09, 0.32])
- The effect of time point [2nd] is statistically significant and negative (beta = -0.78, 95% CI [-1.43, -0.13], t(848) = -2.34, p = 0.019; Std. beta = -0.15, 95% CI [-0.28, -0.02])
- The effect of time point [3rd] is statistically non-significant and negative (beta = -0.63, 95% CI [-1.31, 0.04], t(848) = -1.84, p = 0.065; Std. beta = -0.12, 95% CI [-0.25, 7.65e-03])
- The interaction effect of time point [2nd] on group [treatment] is statistically significant and negative (beta = -1.73, 95% CI [-2.73, -0.74], t(848) = -3.42, p < .001; Std. beta = -0.33, 95% CI [-0.52, -0.14])
- The interaction effect of time point [3rd] on group [treatment] is statistically significant and negative (beta = -2.45, 95% CI [-3.46, -1.44], t(848) = -4.74, p < .001; Std. beta = -0.47, 95% CI [-0.67, -0.28])
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.
gad
We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict gad with group and time_point (formula: gad ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.67) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st , is at 7.54 (95% CI [6.79, 8.28], t(848) = 19.74, p < .001). Within this model:
- The effect of group [treatment] is statistically non-significant and positive (beta = 0.48, 95% CI [-0.58, 1.54], t(848) = 0.89, p = 0.373; Std. beta = 0.09, 95% CI [-0.11, 0.30])
- The effect of time point [2nd] is statistically non-significant and negative (beta = -0.44, 95% CI [-1.11, 0.23], t(848) = -1.29, p = 0.198; Std. beta = -0.08, 95% CI [-0.21, 0.04])
- The effect of time point [3rd] is statistically non-significant and negative (beta = -0.60, 95% CI [-1.28, 0.09], t(848) = -1.69, p = 0.091; Std. beta = -0.11, 95% CI [-0.25, 0.02])
- The interaction effect of time point [2nd] on group [treatment] is statistically significant and negative (beta = -2.07, 95% CI [-3.09, -1.06], t(848) = -4.00, p < .001; Std. beta = -0.40, 95% CI [-0.60, -0.20])
- The interaction effect of time point [3rd] on group [treatment] is statistically significant and negative (beta = -2.37, 95% CI [-3.41, -1.33], t(848) = -4.47, p < .001; Std. beta = -0.46, 95% CI [-0.66, -0.26])
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.
wsas
We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict wsas with group and time_point (formula: wsas ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.64) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st , is at 16.77 (95% CI [15.30, 18.24], t(848) = 22.41, p < .001). Within this model:
- The effect of group [treatment] is statistically non-significant and negative (beta = -0.08, 95% CI [-2.16, 1.99], t(848) = -0.08, p = 0.937; Std. beta = -8.24e-03, 95% CI [-0.21, 0.20])
- The effect of time point [2nd] is statistically non-significant and negative (beta = -0.82, 95% CI [-2.18, 0.54], t(848) = -1.18, p = 0.239; Std. beta = -0.08, 95% CI [-0.21, 0.05])
- The effect of time point [3rd] is statistically non-significant and negative (beta = -0.09, 95% CI [-1.49, 1.32], t(848) = -0.12, p = 0.902; Std. beta = -8.73e-03, 95% CI [-0.15, 0.13])
- The interaction effect of time point [2nd] on group [treatment] is statistically significant and negative (beta = -2.95, 95% CI [-5.02, -0.88], t(848) = -2.80, p = 0.005; Std. beta = -0.29, 95% CI [-0.49, -0.09])
- The interaction effect of time point [3rd] on group [treatment] is statistically significant and negative (beta = -4.95, 95% CI [-7.06, -2.83], t(848) = -4.59, p < .001; Std. beta = -0.49, 95% CI [-0.69, -0.28])
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.
shps_arousal
We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict shps_arousal with group and time_point (formula: shps_arousal ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.56) and the part related to the fixed effects alone (marginal R2) is of 0.11. The model’s intercept, corresponding to group = control and time_point = 1st , is at 3.02 (95% CI [2.91, 3.13], t(848) = 54.46, p < .001). Within this model:
- The effect of group [treatment] is statistically significant and positive (beta = 0.16, 95% CI [8.83e-03, 0.32], t(848) = 2.07, p = 0.038; Std. beta = 0.21, 95% CI [0.01, 0.40])
- The effect of time point [2nd] is statistically significant and negative (beta = -0.20, 95% CI [-0.31, -0.08], t(848) = -3.30, p < .001; Std. beta = -0.25, 95% CI [-0.39, -0.10])
- The effect of time point [3rd] is statistically significant and negative (beta = -0.22, 95% CI [-0.34, -0.10], t(848) = -3.58, p < .001; Std. beta = -0.28, 95% CI [-0.43, -0.13])
- The interaction effect of time point [2nd] on group [treatment] is statistically significant and negative (beta = -0.48, 95% CI [-0.65, -0.30], t(848) = -5.33, p < .001; Std. beta = -0.60, 95% CI [-0.83, -0.38])
- The interaction effect of time point [3rd] on group [treatment] is statistically significant and negative (beta = -0.57, 95% CI [-0.74, -0.39], t(848) = -6.18, p < .001; Std. beta = -0.72, 95% CI [-0.94, -0.49])
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.
shps_schedule
We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict shps_schedule with group and time_point (formula: shps_schedule ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.67) and the part related to the fixed effects alone (marginal R2) is of 0.05. The model’s intercept, corresponding to group = control and time_point = 1st , is at 3.53 (95% CI [3.40, 3.66], t(848) = 53.11, p < .001). Within this model:
- The effect of group [treatment] is statistically non-significant and positive (beta = 0.04, 95% CI [-0.14, 0.23], t(848) = 0.44, p = 0.659; Std. beta = 0.05, 95% CI [-0.16, 0.25])
- The effect of time point [2nd] is statistically non-significant and negative (beta = -0.10, 95% CI [-0.22, 0.02], t(848) = -1.68, p = 0.093; Std. beta = -0.11, 95% CI [-0.24, 0.02])
- The effect of time point [3rd] is statistically significant and negative (beta = -0.13, 95% CI [-0.25, -0.01], t(848) = -2.14, p = 0.033; Std. beta = -0.14, 95% CI [-0.28, -0.01])
- The interaction effect of time point [2nd] on group [treatment] is statistically significant and negative (beta = -0.34, 95% CI [-0.52, -0.17], t(848) = -3.79, p < .001; Std. beta = -0.38, 95% CI [-0.57, -0.18])
- The interaction effect of time point [3rd] on group [treatment] is statistically significant and negative (beta = -0.43, 95% CI [-0.61, -0.24], t(848) = -4.57, p < .001; Std. beta = -0.46, 95% CI [-0.66, -0.27])
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.
shps_behavior
We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict shps_behavior with group and time_point (formula: shps_behavior ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.58) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st , is at 1.99 (95% CI [1.89, 2.08], t(848) = 39.00, p < .001). Within this model:
- The effect of group [treatment] is statistically non-significant and positive (beta = 0.13, 95% CI [-8.87e-03, 0.27], t(848) = 1.84, p = 0.066; Std. beta = 0.19, 95% CI [-0.01, 0.40])
- The effect of time point [2nd] is statistically non-significant and positive (beta = 0.02, 95% CI [-0.07, 0.12], t(848) = 0.48, p = 0.629; Std. beta = 0.04, 95% CI [-0.11, 0.18])
- The effect of time point [3rd] is statistically non-significant and positive (beta = 9.23e-03, 95% CI [-0.09, 0.11], t(848) = 0.18, p = 0.860; Std. beta = 0.01, 95% CI [-0.14, 0.16])
- The interaction effect of time point [2nd] on group [treatment] is statistically significant and negative (beta = -0.24, 95% CI [-0.39, -0.09], t(848) = -3.18, p = 0.001; Std. beta = -0.35, 95% CI [-0.57, -0.14])
- The interaction effect of time point [3rd] on group [treatment] is statistically significant and negative (beta = -0.33, 95% CI [-0.49, -0.18], t(848) = -4.25, p < .001; Std. beta = -0.48, 95% CI [-0.71, -0.26])
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.
shps_environment
We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict shps_environment with group and time_point (formula: shps_environment ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.59) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st , is at 2.33 (95% CI [2.21, 2.45], t(848) = 38.44, p < .001). Within this model:
- The effect of group [treatment] is statistically non-significant and negative (beta = -0.06, 95% CI [-0.23, 0.11], t(848) = -0.72, p = 0.469; Std. beta = -0.08, 95% CI [-0.28, 0.13])
- The effect of time point [2nd] is statistically non-significant and negative (beta = -0.06, 95% CI [-0.18, 0.06], t(848) = -0.97, p = 0.331; Std. beta = -0.07, 95% CI [-0.22, 0.07])
- The effect of time point [3rd] is statistically non-significant and negative (beta = -0.06, 95% CI [-0.18, 0.06], t(848) = -0.99, p = 0.322; Std. beta = -0.08, 95% CI [-0.22, 0.07])
- The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.09, 95% CI [-0.26, 0.09], t(848) = -0.94, p = 0.347; Std. beta = -0.10, 95% CI [-0.32, 0.11])
- The interaction effect of time point [3rd] on group [treatment] is statistically significant and negative (beta = -0.26, 95% CI [-0.44, -0.08], t(848) = -2.78, p = 0.005; Std. beta = -0.32, 95% CI [-0.54, -0.09])
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.
dbas_consequence
We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict dbas_consequence with group and time_point (formula: dbas_consequence ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.62) and the part related to the fixed effects alone (marginal R2) is of 0.12. The model’s intercept, corresponding to group = control and time_point = 1st , is at 6.59 (95% CI [6.31, 6.86], t(848) = 46.90, p < .001). Within this model:
- The effect of group [treatment] is statistically non-significant and positive (beta = 0.05, 95% CI [-0.34, 0.44], t(848) = 0.27, p = 0.787; Std. beta = 0.03, 95% CI [-0.17, 0.22])
- The effect of time point [2nd] is statistically significant and negative (beta = -0.34, 95% CI [-0.61, -0.06], t(848) = -2.39, p = 0.017; Std. beta = -0.17, 95% CI [-0.30, -0.03])
- The effect of time point [3rd] is statistically significant and negative (beta = -0.67, 95% CI [-0.95, -0.38], t(848) = -4.61, p < .001; Std. beta = -0.33, 95% CI [-0.47, -0.19])
- The interaction effect of time point [2nd] on group [treatment] is statistically significant and negative (beta = -1.11, 95% CI [-1.53, -0.69], t(848) = -5.22, p < .001; Std. beta = -0.55, 95% CI [-0.76, -0.34])
- The interaction effect of time point [3rd] on group [treatment] is statistically significant and negative (beta = -1.30, 95% CI [-1.73, -0.87], t(848) = -5.98, p < .001; Std. beta = -0.65, 95% CI [-0.86, -0.43])
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.
dbas_worry
We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict dbas_worry with group and time_point (formula: dbas_worry ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.53) and the part related to the fixed effects alone (marginal R2) is of 0.16. The model’s intercept, corresponding to group = control and time_point = 1st , is at 14.20 (95% CI [13.65, 14.76], t(848) = 50.06, p < .001). Within this model:
- The effect of group [treatment] is statistically non-significant and positive (beta = 0.34, 95% CI [-0.45, 1.13], t(848) = 0.85, p = 0.396; Std. beta = 0.08, 95% CI [-0.11, 0.27])
- The effect of time point [2nd] is statistically significant and negative (beta = -1.23, 95% CI [-1.86, -0.60], t(848) = -3.81, p < .001; Std. beta = -0.30, 95% CI [-0.45, -0.14])
- The effect of time point [3rd] is statistically significant and negative (beta = -1.84, 95% CI [-2.50, -1.19], t(848) = -5.54, p < .001; Std. beta = -0.44, 95% CI [-0.60, -0.29])
- The interaction effect of time point [2nd] on group [treatment] is statistically significant and negative (beta = -2.71, 95% CI [-3.67, -1.76], t(848) = -5.57, p < .001; Std. beta = -0.65, 95% CI [-0.88, -0.42])
- The interaction effect of time point [3rd] on group [treatment] is statistically significant and negative (beta = -2.87, 95% CI [-3.84, -1.90], t(848) = -5.77, p < .001; Std. beta = -0.69, 95% CI [-0.93, -0.46])
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.
dbas_expectation
We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict dbas_expectation with group and time_point (formula: dbas_expectation ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 0.11. The model’s intercept, corresponding to group = control and time_point = 1st , is at 7.17 (95% CI [6.84, 7.51], t(848) = 41.62, p < .001). Within this model:
- The effect of group [treatment] is statistically non-significant and negative (beta = -0.28, 95% CI [-0.76, 0.19], t(848) = -1.17, p = 0.242; Std. beta = -0.12, 95% CI [-0.31, 0.08])
- The effect of time point [2nd] is statistically non-significant and negative (beta = -0.34, 95% CI [-0.69, 1.84e-03], t(848) = -1.95, p = 0.051; Std. beta = -0.14, 95% CI [-0.28, 7.53e-04])
- The effect of time point [3rd] is statistically significant and negative (beta = -0.77, 95% CI [-1.13, -0.42], t(848) = -4.26, p < .001; Std. beta = -0.32, 95% CI [-0.46, -0.17])
- The interaction effect of time point [2nd] on group [treatment] is statistically significant and negative (beta = -1.25, 95% CI [-1.77, -0.73], t(848) = -4.69, p < .001; Std. beta = -0.51, 95% CI [-0.72, -0.30])
- The interaction effect of time point [3rd] on group [treatment] is statistically significant and negative (beta = -1.28, 95% CI [-1.82, -0.75], t(848) = -4.72, p < .001; Std. beta = -0.53, 95% CI [-0.74, -0.31])
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.
dbas_medication
We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict dbas_medication with group and time_point (formula: dbas_medication ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.56) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st , is at 3.15 (95% CI [2.83, 3.46], t(848) = 19.54, p < .001). Within this model:
- The effect of group [treatment] is statistically non-significant and positive (beta = 0.09, 95% CI [-0.36, 0.54], t(848) = 0.39, p = 0.695; Std. beta = 0.04, 95% CI [-0.17, 0.25])
- The effect of time point [2nd] is statistically significant and positive (beta = 0.37, 95% CI [0.04, 0.69], t(848) = 2.23, p = 0.026; Std. beta = 0.17, 95% CI [0.02, 0.32])
- The effect of time point [3rd] is statistically non-significant and positive (beta = 0.31, 95% CI [-0.02, 0.64], t(848) = 1.83, p = 0.068; Std. beta = 0.14, 95% CI [-0.01, 0.30])
- The interaction effect of time point [2nd] on group [treatment] is statistically significant and negative (beta = -0.66, 95% CI [-1.15, -0.18], t(848) = -2.67, p = 0.008; Std. beta = -0.31, 95% CI [-0.53, -0.08])
- The interaction effect of time point [3rd] on group [treatment] is statistically significant and negative (beta = -0.86, 95% CI [-1.36, -0.36], t(848) = -3.39, p < .001; Std. beta = -0.40, 95% CI [-0.63, -0.17])
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.
psas_somatic
We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict psas_somatic with group and time_point (formula: psas_somatic ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.64) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st , is at 1.86 (95% CI [1.76, 1.96], t(848) = 36.72, p < .001). Within this model:
- The effect of group [treatment] is statistically non-significant and positive (beta = 0.04, 95% CI [-0.10, 0.19], t(848) = 0.62, p = 0.533; Std. beta = 0.07, 95% CI [-0.14, 0.27])
- The effect of time point [2nd] is statistically significant and positive (beta = 0.14, 95% CI [0.05, 0.24], t(848) = 3.03, p = 0.002; Std. beta = 0.21, 95% CI [0.07, 0.35])
- The effect of time point [3rd] is statistically non-significant and positive (beta = 5.72e-03, 95% CI [-0.09, 0.10], t(848) = 0.12, p = 0.907; Std. beta = 8.37e-03, 95% CI [-0.13, 0.15])
- The interaction effect of time point [2nd] on group [treatment] is statistically significant and negative (beta = -0.31, 95% CI [-0.45, -0.17], t(848) = -4.27, p < .001; Std. beta = -0.45, 95% CI [-0.65, -0.24])
- The interaction effect of time point [3rd] on group [treatment] is statistically significant and negative (beta = -0.24, 95% CI [-0.38, -0.09], t(848) = -3.24, p = 0.001; Std. beta = -0.35, 95% CI [-0.56, -0.14])
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.
psas_cognitive
We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict psas_cognitive with group and time_point (formula: psas_cognitive ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.61) and the part related to the fixed effects alone (marginal R2) is of 0.09. The model’s intercept, corresponding to group = control and time_point = 1st , is at 2.87 (95% CI [2.75, 3.00], t(848) = 45.24, p < .001). Within this model:
- The effect of group [treatment] is statistically non-significant and positive (beta = 0.10, 95% CI [-0.08, 0.28], t(848) = 1.10, p = 0.269; Std. beta = 0.11, 95% CI [-0.09, 0.31])
- The effect of time point [2nd] is statistically significant and negative (beta = -0.20, 95% CI [-0.33, -0.08], t(848) = -3.20, p = 0.001; Std. beta = -0.23, 95% CI [-0.37, -0.09])
- The effect of time point [3rd] is statistically significant and negative (beta = -0.36, 95% CI [-0.49, -0.23], t(848) = -5.52, p < .001; Std. beta = -0.41, 95% CI [-0.55, -0.26])
- The interaction effect of time point [2nd] on group [treatment] is statistically significant and negative (beta = -0.43, 95% CI [-0.62, -0.24], t(848) = -4.49, p < .001; Std. beta = -0.49, 95% CI [-0.70, -0.28])
- The interaction effect of time point [3rd] on group [treatment] is statistically significant and negative (beta = -0.41, 95% CI [-0.60, -0.21], t(848) = -4.12, p < .001; Std. beta = -0.46, 95% CI [-0.67, -0.24])
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.
psqi_global
We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict psqi_global with group and time_point (formula: psqi_global ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.56) and the part related to the fixed effects alone (marginal R2) is of 0.15. The model’s intercept, corresponding to group = control and time_point = 1st , is at 10.72 (95% CI [10.26, 11.19], t(848) = 45.23, p < .001). Within this model:
- The effect of group [treatment] is statistically non-significant and positive (beta = 0.29, 95% CI [-0.37, 0.95], t(848) = 0.87, p = 0.386; Std. beta = 0.08, 95% CI [-0.11, 0.27])
- The effect of time point [2nd] is statistically significant and negative (beta = -1.31, 95% CI [-1.82, -0.81], t(848) = -5.09, p < .001; Std. beta = -0.38, 95% CI [-0.53, -0.23])
- The effect of time point [3rd] is statistically significant and negative (beta = -1.31, 95% CI [-1.84, -0.79], t(848) = -4.95, p < .001; Std. beta = -0.38, 95% CI [-0.53, -0.23])
- The interaction effect of time point [2nd] on group [treatment] is statistically significant and negative (beta = -1.86, 95% CI [-2.62, -1.10], t(848) = -4.78, p < .001; Std. beta = -0.54, 95% CI [-0.76, -0.32])
- The interaction effect of time point [3rd] on group [treatment] is statistically significant and negative (beta = -2.44, 95% CI [-3.22, -1.66], t(848) = -6.15, p < .001; Std. beta = -0.71, 95% CI [-0.93, -0.48])
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.
mic_attention
We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict mic_attention with group and time_point (formula: mic_attention ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st , is at 1.30 (95% CI [1.19, 1.41], t(848) = 22.91, p < .001). Within this model:
- The effect of group [treatment] is statistically non-significant and positive (beta = 0.12, 95% CI [-0.04, 0.28], t(848) = 1.52, p = 0.129; Std. beta = 0.16, 95% CI [-0.05, 0.36])
- The effect of time point [2nd] is statistically non-significant and negative (beta = -0.02, 95% CI [-0.13, 0.09], t(848) = -0.39, p = 0.694; Std. beta = -0.03, 95% CI [-0.17, 0.11])
- The effect of time point [3rd] is statistically non-significant and positive (beta = 0.03, 95% CI [-0.08, 0.15], t(848) = 0.59, p = 0.558; Std. beta = 0.04, 95% CI [-0.10, 0.19])
- The interaction effect of time point [2nd] on group [treatment] is statistically significant and negative (beta = -0.25, 95% CI [-0.41, -0.08], t(848) = -2.95, p = 0.003; Std. beta = -0.32, 95% CI [-0.54, -0.11])
- The interaction effect of time point [3rd] on group [treatment] is statistically significant and negative (beta = -0.39, 95% CI [-0.56, -0.22], t(848) = -4.51, p < .001; Std. beta = -0.50, 95% CI [-0.72, -0.28])
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.
mic_executive
We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict mic_executive with group and time_point (formula: mic_executive ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.63) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st , is at 1.28 (95% CI [1.17, 1.39], t(848) = 22.00, p < .001). Within this model:
- The effect of group [treatment] is statistically non-significant and positive (beta = 0.07, 95% CI [-0.09, 0.23], t(848) = 0.82, p = 0.415; Std. beta = 0.08, 95% CI [-0.12, 0.29])
- The effect of time point [2nd] is statistically non-significant and negative (beta = -0.03, 95% CI [-0.14, 0.07], t(848) = -0.62, p = 0.537; Std. beta = -0.04, 95% CI [-0.18, 0.09])
- The effect of time point [3rd] is statistically non-significant and negative (beta = -0.05, 95% CI [-0.16, 0.06], t(848) = -0.90, p = 0.368; Std. beta = -0.06, 95% CI [-0.20, 0.08])
- The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.16, 95% CI [-0.32, 2.51e-03], t(848) = -1.93, p = 0.054; Std. beta = -0.20, 95% CI [-0.41, 3.18e-03])
- The interaction effect of time point [3rd] on group [treatment] is statistically significant and negative (beta = -0.27, 95% CI [-0.44, -0.10], t(848) = -3.20, p = 0.001; Std. beta = -0.34, 95% CI [-0.55, -0.13])
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.
mic_memory
We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict mic_memory with group and time_point (formula: mic_memory ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.67) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st , is at 1.33 (95% CI [1.22, 1.44], t(848) = 23.30, p < .001). Within this model:
- The effect of group [treatment] is statistically non-significant and positive (beta = 0.07, 95% CI [-0.09, 0.22], t(848) = 0.81, p = 0.417; Std. beta = 0.08, 95% CI [-0.12, 0.29])
- The effect of time point [2nd] is statistically non-significant and positive (beta = 0.03, 95% CI [-0.07, 0.13], t(848) = 0.62, p = 0.538; Std. beta = 0.04, 95% CI [-0.09, 0.17])
- The effect of time point [3rd] is statistically non-significant and negative (beta = -0.07, 95% CI [-0.17, 0.04], t(848) = -1.23, p = 0.217; Std. beta = -0.08, 95% CI [-0.22, 0.05])
- The interaction effect of time point [2nd] on group [treatment] is statistically significant and negative (beta = -0.28, 95% CI [-0.43, -0.12], t(848) = -3.55, p < .001; Std. beta = -0.35, 95% CI [-0.55, -0.16])
- The interaction effect of time point [3rd] on group [treatment] is statistically significant and negative (beta = -0.22, 95% CI [-0.37, -0.06], t(848) = -2.75, p = 0.006; Std. beta = -0.28, 95% CI [-0.48, -0.08])
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.
nb_pcs
We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict nb_pcs with group and time_point (formula: nb_pcs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.66) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st , is at 46.33 (95% CI [45.04, 47.63], t(848) = 70.36, p < .001). Within this model:
- The effect of group [treatment] is statistically non-significant and negative (beta = -0.14, 95% CI [-1.96, 1.69], t(848) = -0.15, p = 0.881; Std. beta = -0.02, 95% CI [-0.22, 0.19])
- The effect of time point [2nd] is statistically non-significant and negative (beta = -0.87, 95% CI [-2.03, 0.29], t(848) = -1.48, p = 0.140; Std. beta = -0.10, 95% CI [-0.23, 0.03])
- The effect of time point [3rd] is statistically non-significant and negative (beta = -0.79, 95% CI [-1.99, 0.40], t(848) = -1.30, p = 0.194; Std. beta = -0.09, 95% CI [-0.22, 0.05])
- The interaction effect of time point [2nd] on group [treatment] is statistically significant and positive (beta = 2.76, 95% CI [1.00, 4.52], t(848) = 3.08, p = 0.002; Std. beta = 0.31, 95% CI [0.11, 0.51])
- The interaction effect of time point [3rd] on group [treatment] is statistically significant and positive (beta = 3.21, 95% CI [1.41, 5.00], t(848) = 3.50, p < .001; Std. beta = 0.36, 95% CI [0.16, 0.56])
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.
nb_mcs
We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict nb_mcs with group and time_point (formula: nb_mcs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.63) and the part related to the fixed effects alone (marginal R2) is of 0.06. The model’s intercept, corresponding to group = control and time_point = 1st , is at 39.90 (95% CI [38.39, 41.41], t(848) = 51.75, p < .001). Within this model:
- The effect of group [treatment] is statistically non-significant and positive (beta = 0.09, 95% CI [-2.05, 2.22], t(848) = 0.08, p = 0.938; Std. beta = 7.97e-03, 95% CI [-0.19, 0.21])
- The effect of time point [2nd] is statistically significant and positive (beta = 2.00, 95% CI [0.55, 3.45], t(848) = 2.71, p = 0.007; Std. beta = 0.19, 95% CI [0.05, 0.32])
- The effect of time point [3rd] is statistically significant and positive (beta = 2.26, 95% CI [0.76, 3.76], t(848) = 2.96, p = 0.003; Std. beta = 0.21, 95% CI [0.07, 0.35])
- The interaction effect of time point [2nd] on group [treatment] is statistically significant and positive (beta = 3.57, 95% CI [1.37, 5.77], t(848) = 3.18, p = 0.001; Std. beta = 0.33, 95% CI [0.13, 0.54])
- The interaction effect of time point [3rd] on group [treatment] is statistically significant and positive (beta = 4.67, 95% CI [2.43, 6.92], t(848) = 4.08, p < .001; Std. beta = 0.44, 95% CI [0.23, 0.65])
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.
Likelihood ratio tests
outcome | model | npar | AIC | BIC | logLik | deviance | Chisq | Df | p |
isi | null | 3 | 4,932.749 | 4,947.006 | -2,463.374 | 4,926.749 | |||
isi | random | 8 | 4,600.914 | 4,638.932 | -2,292.457 | 4,584.914 | 341.835 | 5 | 0.000 |
who | null | 3 | 4,666.709 | 4,680.966 | -2,330.354 | 4,660.709 | |||
who | random | 8 | 4,601.465 | 4,639.484 | -2,292.733 | 4,585.465 | 75.243 | 5 | 0.000 |
phq | null | 3 | 4,943.897 | 4,958.154 | -2,468.948 | 4,937.897 | |||
phq | random | 8 | 4,877.631 | 4,915.649 | -2,430.816 | 4,861.631 | 76.265 | 5 | 0.000 |
gad | null | 3 | 4,962.704 | 4,976.961 | -2,478.352 | 4,956.704 | |||
gad | random | 8 | 4,904.976 | 4,942.994 | -2,444.488 | 4,888.976 | 67.728 | 5 | 0.000 |
wsas | null | 3 | 6,128.933 | 6,143.189 | -3,061.466 | 6,122.933 | |||
wsas | random | 8 | 6,091.587 | 6,129.605 | -3,037.793 | 6,075.587 | 47.346 | 5 | 0.000 |
shps_arousal | null | 3 | 1,902.889 | 1,917.146 | -948.444 | 1,896.889 | |||
shps_arousal | random | 8 | 1,752.117 | 1,790.135 | -868.058 | 1,736.117 | 160.772 | 5 | 0.000 |
shps_schedule | null | 3 | 1,988.828 | 2,003.085 | -991.414 | 1,982.828 | |||
shps_schedule | random | 8 | 1,921.575 | 1,959.593 | -952.787 | 1,905.575 | 77.253 | 5 | 0.000 |
shps_behavior | null | 3 | 1,569.423 | 1,583.679 | -781.711 | 1,563.423 | |||
shps_behavior | random | 8 | 1,546.795 | 1,584.813 | -765.398 | 1,530.795 | 32.627 | 5 | 0.000 |
shps_environment | null | 3 | 1,857.034 | 1,871.291 | -925.517 | 1,851.034 | |||
shps_environment | random | 8 | 1,841.651 | 1,879.669 | -912.825 | 1,825.651 | 25.384 | 5 | 0.000 |
dbas_consequence | null | 3 | 3,449.397 | 3,463.654 | -1,721.699 | 3,443.397 | |||
dbas_consequence | random | 8 | 3,289.747 | 3,327.766 | -1,636.874 | 3,273.747 | 169.650 | 5 | 0.000 |
dbas_worry | null | 3 | 4,787.904 | 4,802.161 | -2,390.952 | 4,781.904 | |||
dbas_worry | random | 8 | 4,594.198 | 4,632.216 | -2,289.099 | 4,578.198 | 203.706 | 5 | 0.000 |
dbas_expectation | null | 3 | 3,783.123 | 3,797.380 | -1,888.562 | 3,777.123 | |||
dbas_expectation | random | 8 | 3,656.069 | 3,694.087 | -1,820.035 | 3,640.069 | 137.054 | 5 | 0.000 |
dbas_medication | null | 3 | 3,546.636 | 3,560.893 | -1,770.318 | 3,540.636 | |||
dbas_medication | random | 8 | 3,540.146 | 3,578.165 | -1,762.073 | 3,524.146 | 16.490 | 5 | 0.006 |
psas_somatic | null | 3 | 1,507.592 | 1,521.849 | -750.796 | 1,501.592 | |||
psas_somatic | random | 8 | 1,485.470 | 1,523.488 | -734.735 | 1,469.470 | 32.122 | 5 | 0.000 |
psas_cognitive | null | 3 | 2,067.718 | 2,081.975 | -1,030.859 | 2,061.718 | |||
psas_cognitive | random | 8 | 1,933.524 | 1,971.542 | -958.762 | 1,917.524 | 144.195 | 5 | 0.000 |
psqi_global | null | 3 | 4,446.260 | 4,460.517 | -2,220.130 | 4,440.260 | |||
psqi_global | random | 8 | 4,252.480 | 4,290.498 | -2,118.240 | 4,236.480 | 203.780 | 5 | 0.000 |
mic_attention | null | 3 | 1,741.497 | 1,755.754 | -867.748 | 1,735.497 | |||
mic_attention | random | 8 | 1,716.784 | 1,754.802 | -850.392 | 1,700.784 | 34.713 | 5 | 0.000 |
mic_executive | null | 3 | 1,741.110 | 1,755.366 | -867.555 | 1,735.110 | |||
mic_executive | random | 8 | 1,723.813 | 1,761.832 | -853.907 | 1,707.813 | 27.296 | 5 | 0.000 |
mic_memory | null | 3 | 1,675.487 | 1,689.744 | -834.744 | 1,669.487 | |||
mic_memory | random | 8 | 1,654.478 | 1,692.497 | -819.239 | 1,638.478 | 31.009 | 5 | 0.000 |
nb_pcs | null | 3 | 5,850.561 | 5,864.818 | -2,922.281 | 5,844.561 | |||
nb_pcs | random | 8 | 5,841.498 | 5,879.516 | -2,912.749 | 5,825.498 | 19.063 | 5 | 0.002 |
nb_mcs | null | 3 | 6,244.820 | 6,259.076 | -3,119.410 | 6,238.820 | |||
nb_mcs | random | 8 | 6,169.779 | 6,207.797 | -3,076.890 | 6,153.779 | 85.041 | 5 | 0.000 |
Post hoc analysis
Table
outcome | time | control | treatment | between | |||||
n | estimate | within es | n | estimate | within es | p | es | ||
isi | 1st | 179 | 13.53 ± 3.82 | 179 | 13.40 ± 3.82 | 0.751 | 0.045 | ||
isi | 2nd | 148 | 11.07 ± 3.76 | 0.863 | 109 | 7.98 ± 3.67 | 1.904 | 0.000 | 1.086 |
isi | 3rd | 136 | 10.68 ± 3.72 | 1.000 | 105 | 7.57 ± 3.66 | 2.050 | 0.000 | 1.095 |
who | 1st | 179 | 9.82 ± 4.09 | 179 | 9.98 ± 4.09 | 0.708 | -0.062 | ||
who | 2nd | 148 | 10.55 ± 3.96 | -0.278 | 109 | 12.11 ± 3.80 | -0.813 | 0.001 | -0.597 |
who | 3rd | 136 | 10.74 ± 3.90 | -0.351 | 105 | 12.54 ± 3.78 | -0.976 | 0.000 | -0.687 |
phq | 1st | 179 | 8.21 ± 5.07 | 179 | 8.80 ± 5.07 | 0.269 | -0.204 | ||
phq | 2nd | 148 | 7.43 ± 4.87 | 0.268 | 109 | 6.29 ± 4.60 | 0.864 | 0.055 | 0.393 |
phq | 3rd | 136 | 7.58 ± 4.77 | 0.218 | 105 | 5.72 ± 4.56 | 1.060 | 0.002 | 0.639 |
gad | 1st | 179 | 7.54 ± 5.11 | 179 | 8.02 ± 5.11 | 0.374 | -0.161 | ||
gad | 2nd | 148 | 7.10 ± 4.91 | 0.148 | 109 | 5.51 ± 4.65 | 0.843 | 0.008 | 0.534 |
gad | 3rd | 136 | 6.94 ± 4.81 | 0.200 | 105 | 5.05 ± 4.62 | 0.994 | 0.002 | 0.633 |
wsas | 1st | 179 | 16.77 ± 10.01 | 179 | 16.69 ± 10.01 | 0.937 | 0.014 | ||
wsas | 2nd | 148 | 15.95 ± 9.66 | 0.135 | 109 | 12.92 ± 9.21 | 0.620 | 0.011 | 0.499 |
wsas | 3rd | 136 | 16.68 ± 9.49 | 0.015 | 105 | 11.65 ± 9.14 | 0.828 | 0.000 | 0.827 |
shps_arousal | 1st | 179 | 3.02 ± 0.74 | 179 | 3.18 ± 0.74 | 0.039 | -0.312 | ||
shps_arousal | 2nd | 148 | 2.83 ± 0.73 | 0.375 | 109 | 2.51 ± 0.70 | 1.291 | 0.001 | 0.604 |
shps_arousal | 3rd | 136 | 2.80 ± 0.72 | 0.420 | 105 | 2.40 ± 0.70 | 1.504 | 0.000 | 0.773 |
shps_schedule | 1st | 179 | 3.53 ± 0.89 | 179 | 3.58 ± 0.89 | 0.659 | -0.079 | ||
shps_schedule | 2nd | 148 | 3.43 ± 0.86 | 0.192 | 109 | 3.13 ± 0.81 | 0.850 | 0.004 | 0.579 |
shps_schedule | 3rd | 136 | 3.40 ± 0.84 | 0.252 | 105 | 3.02 ± 0.81 | 1.064 | 0.000 | 0.732 |
shps_behavior | 1st | 179 | 1.99 ± 0.68 | 179 | 2.12 ± 0.68 | 0.067 | -0.298 | ||
shps_behavior | 2nd | 148 | 2.01 ± 0.66 | -0.055 | 109 | 1.90 ± 0.64 | 0.494 | 0.172 | 0.252 |
shps_behavior | 3rd | 136 | 1.99 ± 0.65 | -0.021 | 105 | 1.79 ± 0.63 | 0.729 | 0.016 | 0.452 |
shps_environment | 1st | 179 | 2.33 ± 0.81 | 179 | 2.27 ± 0.81 | 0.469 | 0.118 | ||
shps_environment | 2nd | 148 | 2.27 ± 0.79 | 0.111 | 109 | 2.13 ± 0.76 | 0.274 | 0.129 | 0.281 |
shps_environment | 3rd | 136 | 2.27 ± 0.78 | 0.116 | 105 | 1.95 ± 0.75 | 0.607 | 0.001 | 0.609 |
dbas_consequence | 1st | 179 | 6.59 ± 1.88 | 179 | 6.64 ± 1.88 | 0.787 | -0.044 | ||
dbas_consequence | 2nd | 148 | 6.25 ± 1.83 | 0.273 | 109 | 5.19 ± 1.76 | 1.174 | 0.000 | 0.857 |
dbas_consequence | 3rd | 136 | 5.92 ± 1.80 | 0.542 | 105 | 4.67 ± 1.75 | 1.597 | 0.000 | 1.011 |
dbas_worry | 1st | 179 | 14.20 ± 3.80 | 179 | 14.54 ± 3.80 | 0.396 | -0.120 | ||
dbas_worry | 2nd | 148 | 12.97 ± 3.73 | 0.432 | 109 | 10.60 ± 3.65 | 1.384 | 0.000 | 0.832 |
dbas_worry | 3rd | 136 | 12.36 ± 3.70 | 0.647 | 105 | 9.83 ± 3.64 | 1.653 | 0.000 | 0.887 |
dbas_expectation | 1st | 179 | 7.17 ± 2.31 | 179 | 6.89 ± 2.31 | 0.243 | 0.185 | ||
dbas_expectation | 2nd | 148 | 6.83 ± 2.24 | 0.222 | 109 | 5.30 ± 2.17 | 1.030 | 0.000 | 0.993 |
dbas_expectation | 3rd | 136 | 6.40 ± 2.21 | 0.500 | 105 | 4.83 ± 2.15 | 1.331 | 0.000 | 1.016 |
dbas_medication | 1st | 179 | 3.15 ± 2.15 | 179 | 3.24 ± 2.15 | 0.695 | -0.062 | ||
dbas_medication | 2nd | 148 | 3.51 ± 2.10 | -0.254 | 109 | 2.94 ± 2.02 | 0.206 | 0.027 | 0.398 |
dbas_medication | 3rd | 136 | 3.46 ± 2.07 | -0.214 | 105 | 2.69 ± 2.01 | 0.382 | 0.004 | 0.535 |
psas_somatic | 1st | 179 | 1.86 ± 0.68 | 179 | 1.91 ± 0.68 | 0.533 | -0.108 | ||
psas_somatic | 2nd | 148 | 2.00 ± 0.65 | -0.347 | 109 | 1.74 ± 0.62 | 0.393 | 0.001 | 0.632 |
psas_somatic | 3rd | 136 | 1.87 ± 0.64 | -0.014 | 105 | 1.67 ± 0.62 | 0.561 | 0.019 | 0.467 |
psas_cognitive | 1st | 179 | 2.87 ± 0.85 | 179 | 2.97 ± 0.85 | 0.270 | -0.177 | ||
psas_cognitive | 2nd | 148 | 2.67 ± 0.83 | 0.365 | 109 | 2.33 ± 0.79 | 1.141 | 0.001 | 0.599 |
psas_cognitive | 3rd | 136 | 2.51 ± 0.81 | 0.649 | 105 | 2.20 ± 0.79 | 1.376 | 0.003 | 0.550 |
psqi_global | 1st | 179 | 10.72 ± 3.17 | 179 | 11.01 ± 3.17 | 0.386 | -0.128 | ||
psqi_global | 2nd | 148 | 9.41 ± 3.11 | 0.578 | 109 | 7.84 ± 3.02 | 1.398 | 0.000 | 0.692 |
psqi_global | 3rd | 136 | 9.41 ± 3.07 | 0.579 | 105 | 7.25 ± 3.01 | 1.656 | 0.000 | 0.949 |
mic_attention | 1st | 179 | 1.30 ± 0.76 | 179 | 1.42 ± 0.76 | 0.130 | -0.250 | ||
mic_attention | 2nd | 148 | 1.28 ± 0.73 | 0.045 | 109 | 1.15 ± 0.70 | 0.554 | 0.165 | 0.259 |
mic_attention | 3rd | 136 | 1.33 ± 0.72 | -0.069 | 105 | 1.07 ± 0.70 | 0.728 | 0.004 | 0.546 |
mic_executive | 1st | 179 | 1.28 ± 0.78 | 179 | 1.35 ± 0.78 | 0.415 | -0.141 | ||
mic_executive | 2nd | 148 | 1.25 ± 0.75 | 0.071 | 109 | 1.15 ± 0.72 | 0.405 | 0.318 | 0.194 |
mic_executive | 3rd | 136 | 1.23 ± 0.74 | 0.106 | 105 | 1.03 ± 0.71 | 0.673 | 0.031 | 0.426 |
mic_memory | 1st | 179 | 1.33 ± 0.77 | 179 | 1.40 ± 0.77 | 0.417 | -0.147 | ||
mic_memory | 2nd | 148 | 1.36 ± 0.74 | -0.071 | 109 | 1.15 ± 0.70 | 0.548 | 0.020 | 0.471 |
mic_memory | 3rd | 136 | 1.27 ± 0.72 | 0.146 | 105 | 1.12 ± 0.69 | 0.634 | 0.097 | 0.341 |
nb_pcs | 1st | 179 | 46.33 ± 8.81 | 179 | 46.20 ± 8.81 | 0.882 | 0.027 | ||
nb_pcs | 2nd | 148 | 45.46 ± 8.48 | 0.169 | 109 | 48.08 ± 8.03 | -0.366 | 0.012 | -0.508 |
nb_pcs | 3rd | 136 | 45.54 ± 8.31 | 0.153 | 105 | 48.61 ± 7.97 | -0.469 | 0.004 | -0.595 |
nb_mcs | 1st | 179 | 39.90 ± 10.31 | 179 | 39.98 ± 10.31 | 0.938 | -0.013 | ||
nb_mcs | 2nd | 148 | 41.90 ± 9.98 | -0.309 | 109 | 45.56 ± 9.55 | -0.860 | 0.003 | -0.564 |
nb_mcs | 3rd | 136 | 42.16 ± 9.81 | -0.349 | 105 | 46.91 ± 9.49 | -1.070 | 0.000 | -0.734 |
Between group
isi
1st
t(640.87) = -0.32, p = 0.751, Cohen d = 0.05, 95% CI (-0.92 to 0.67)
2st
t(756.19) = -6.60, p = 0.000, Cohen d = 1.09, 95% CI (-4.01 to -2.17)
3rd
t(774.11) = -6.51, p = 0.000, Cohen d = 1.09, 95% CI (-4.06 to -2.18)
who
1st
t(548.22) = 0.38, p = 0.708, Cohen d = -0.06, 95% CI (-0.69 to 1.01)
2st
t(686.86) = 3.20, p = 0.001, Cohen d = -0.60, 95% CI (0.60 to 2.52)
3rd
t(708.71) = 3.62, p = 0.000, Cohen d = -0.69, 95% CI (0.82 to 2.78)
phq
1st
t(500.79) = 1.11, p = 0.269, Cohen d = -0.20, 95% CI (-0.46 to 1.64)
2st
t(636.30) = -1.92, p = 0.055, Cohen d = 0.39, 95% CI (-2.31 to 0.03)
3rd
t(657.97) = -3.07, p = 0.002, Cohen d = 0.64, 95% CI (-3.04 to -0.67)
gad
1st
t(506.80) = 0.89, p = 0.374, Cohen d = -0.16, 95% CI (-0.58 to 1.54)
2st
t(643.49) = -2.65, p = 0.008, Cohen d = 0.53, 95% CI (-2.77 to -0.41)
3rd
t(665.30) = -3.09, p = 0.002, Cohen d = 0.63, 95% CI (-3.09 to -0.69)
wsas
1st
t(523.00) = -0.08, p = 0.937, Cohen d = 0.01, 95% CI (-2.16 to 2.00)
2st
t(661.66) = -2.56, p = 0.011, Cohen d = 0.50, 95% CI (-5.37 to -0.71)
3rd
t(683.68) = -4.17, p = 0.000, Cohen d = 0.83, 95% CI (-7.40 to -2.66)
shps_arousal
1st
t(599.94) = 2.07, p = 0.039, Cohen d = -0.31, 95% CI (0.01 to 0.32)
2st
t(729.24) = -3.49, p = 0.001, Cohen d = 0.60, 95% CI (-0.49 to -0.14)
3rd
t(749.39) = -4.38, p = 0.000, Cohen d = 0.77, 95% CI (-0.58 to -0.22)
shps_schedule
1st
t(510.09) = 0.44, p = 0.659, Cohen d = -0.08, 95% CI (-0.14 to 0.23)
2st
t(647.31) = -2.89, p = 0.004, Cohen d = 0.58, 95% CI (-0.51 to -0.10)
3rd
t(669.19) = -3.60, p = 0.000, Cohen d = 0.73, 95% CI (-0.59 to -0.17)
shps_behavior
1st
t(556.53) = 1.84, p = 0.067, Cohen d = -0.30, 95% CI (-0.01 to 0.27)
2st
t(694.44) = -1.37, p = 0.172, Cohen d = 0.25, 95% CI (-0.27 to 0.05)
3rd
t(716.13) = -2.41, p = 0.016, Cohen d = 0.45, 95% CI (-0.36 to -0.04)
shps_environment
1st
t(552.62) = -0.72, p = 0.469, Cohen d = 0.12, 95% CI (-0.23 to 0.11)
2st
t(690.92) = -1.52, p = 0.129, Cohen d = 0.28, 95% CI (-0.34 to 0.04)
3rd
t(712.69) = -3.23, p = 0.001, Cohen d = 0.61, 95% CI (-0.51 to -0.13)
dbas_consequence
1st
t(560.03) = 0.27, p = 0.787, Cohen d = -0.04, 95% CI (-0.34 to 0.44)
2st
t(697.54) = -4.69, p = 0.000, Cohen d = 0.86, 95% CI (-1.50 to -0.61)
3rd
t(719.15) = -5.42, p = 0.000, Cohen d = 1.01, 95% CI (-1.70 to -0.79)
dbas_worry
1st
t(647.46) = 0.85, p = 0.396, Cohen d = -0.12, 95% CI (-0.45 to 1.13)
2st
t(760.10) = -5.10, p = 0.000, Cohen d = 0.83, 95% CI (-3.29 to -1.46)
3rd
t(777.61) = -5.31, p = 0.000, Cohen d = 0.89, 95% CI (-3.46 to -1.59)
dbas_expectation
1st
t(571.34) = -1.17, p = 0.243, Cohen d = 0.18, 95% CI (-0.76 to 0.19)
2st
t(707.17) = -5.52, p = 0.000, Cohen d = 0.99, 95% CI (-2.08 to -0.99)
3rd
t(728.46) = -5.54, p = 0.000, Cohen d = 1.02, 95% CI (-2.12 to -1.01)
dbas_medication
1st
t(571.27) = 0.39, p = 0.695, Cohen d = -0.06, 95% CI (-0.36 to 0.54)
2st
t(707.11) = -2.21, p = 0.027, Cohen d = 0.40, 95% CI (-1.08 to -0.07)
3rd
t(728.40) = -2.92, p = 0.004, Cohen d = 0.53, 95% CI (-1.29 to -0.25)
psas_somatic
1st
t(524.92) = 0.62, p = 0.533, Cohen d = -0.11, 95% CI (-0.10 to 0.19)
2st
t(663.70) = -3.25, p = 0.001, Cohen d = 0.63, 95% CI (-0.42 to -0.10)
3rd
t(685.73) = -2.36, p = 0.019, Cohen d = 0.47, 95% CI (-0.35 to -0.03)
psas_cognitive
1st
t(562.06) = 1.10, p = 0.270, Cohen d = -0.18, 95% CI (-0.08 to 0.28)
2st
t(699.31) = -3.28, p = 0.001, Cohen d = 0.60, 95% CI (-0.54 to -0.13)
3rd
t(720.87) = -2.96, p = 0.003, Cohen d = 0.55, 95% CI (-0.51 to -0.10)
psqi_global
1st
t(612.85) = 0.87, p = 0.386, Cohen d = -0.13, 95% CI (-0.37 to 0.95)
2st
t(738.27) = -4.07, p = 0.000, Cohen d = 0.69, 95% CI (-2.33 to -0.81)
3rd
t(757.79) = -5.46, p = 0.000, Cohen d = 0.95, 95% CI (-2.93 to -1.38)
mic_attention
1st
t(548.32) = 1.52, p = 0.130, Cohen d = -0.25, 95% CI (-0.04 to 0.28)
2st
t(686.95) = -1.39, p = 0.165, Cohen d = 0.26, 95% CI (-0.30 to 0.05)
3rd
t(708.81) = -2.88, p = 0.004, Cohen d = 0.55, 95% CI (-0.45 to -0.08)
mic_executive
1st
t(526.28) = 0.82, p = 0.415, Cohen d = -0.14, 95% CI (-0.09 to 0.23)
2st
t(665.14) = -1.00, p = 0.318, Cohen d = 0.19, 95% CI (-0.27 to 0.09)
3rd
t(687.17) = -2.16, p = 0.031, Cohen d = 0.43, 95% CI (-0.39 to -0.02)
mic_memory
1st
t(506.60) = 0.81, p = 0.417, Cohen d = -0.15, 95% CI (-0.09 to 0.22)
2st
t(643.25) = -2.33, p = 0.020, Cohen d = 0.47, 95% CI (-0.39 to -0.03)
3rd
t(665.06) = -1.66, p = 0.097, Cohen d = 0.34, 95% CI (-0.33 to 0.03)
nb_pcs
1st
t(508.06) = -0.15, p = 0.882, Cohen d = 0.03, 95% CI (-1.97 to 1.69)
2st
t(644.96) = 2.52, p = 0.012, Cohen d = -0.51, 95% CI (0.58 to 4.66)
3rd
t(666.80) = 2.91, p = 0.004, Cohen d = -0.60, 95% CI (1.00 to 5.14)
nb_mcs
1st
t(538.10) = 0.08, p = 0.938, Cohen d = -0.01, 95% CI (-2.06 to 2.23)
2st
t(677.16) = 2.97, p = 0.003, Cohen d = -0.56, 95% CI (1.24 to 6.07)
3rd
t(699.15) = 3.80, p = 0.000, Cohen d = -0.73, 95% CI (2.30 to 7.21)
Within treatment group
isi
1st vs 2st
t(594.74) = -14.88, p = 0.000, Cohen d = 1.90, 95% CI (-6.14 to -4.71)
1st vs 3rd
t(596.42) = -15.80, p = 0.000, Cohen d = 2.05, 95% CI (-6.56 to -5.11)
who
1st vs 2st
t(571.40) = 6.26, p = 0.000, Cohen d = -0.81, 95% CI (1.46 to 2.80)
1st vs 3rd
t(572.14) = 7.41, p = 0.000, Cohen d = -0.98, 95% CI (1.88 to 3.24)
phq
1st vs 2st
t(556.90) = -6.59, p = 0.000, Cohen d = 0.86, 95% CI (-3.26 to -1.76)
1st vs 3rd
t(557.28) = -7.98, p = 0.000, Cohen d = 1.06, 95% CI (-3.84 to -2.32)
gad
1st vs 2st
t(558.86) = -6.44, p = 0.000, Cohen d = 0.84, 95% CI (-3.28 to -1.75)
1st vs 3rd
t(559.28) = -7.49, p = 0.000, Cohen d = 0.99, 95% CI (-3.74 to -2.19)
wsas
1st vs 2st
t(563.96) = -4.75, p = 0.000, Cohen d = 0.62, 95% CI (-5.33 to -2.21)
1st vs 3rd
t(564.49) = -6.25, p = 0.000, Cohen d = 0.83, 95% CI (-6.62 to -3.45)
shps_arousal
1st vs 2st
t(585.10) = -10.02, p = 0.000, Cohen d = 1.29, 95% CI (-0.80 to -0.54)
1st vs 3rd
t(586.33) = -11.51, p = 0.000, Cohen d = 1.50, 95% CI (-0.92 to -0.65)
shps_schedule
1st vs 2st
t(559.92) = -6.50, p = 0.000, Cohen d = 0.85, 95% CI (-0.58 to -0.31)
1st vs 3rd
t(560.36) = -8.01, p = 0.000, Cohen d = 1.06, 95% CI (-0.69 to -0.42)
shps_behavior
1st vs 2st
t(573.74) = -3.81, p = 0.000, Cohen d = 0.49, 95% CI (-0.33 to -0.11)
1st vs 3rd
t(574.55) = -5.54, p = 0.000, Cohen d = 0.73, 95% CI (-0.44 to -0.21)
shps_environment
1st vs 2st
t(572.65) = -2.11, p = 0.071, Cohen d = 0.27, 95% CI (-0.28 to -0.01)
1st vs 3rd
t(573.42) = -4.61, p = 0.000, Cohen d = 0.61, 95% CI (-0.45 to -0.18)
dbas_consequence
1st vs 2st
t(574.71) = -9.05, p = 0.000, Cohen d = 1.17, 95% CI (-1.76 to -1.13)
1st vs 3rd
t(575.54) = -12.14, p = 0.000, Cohen d = 1.60, 95% CI (-2.29 to -1.65)
dbas_worry
1st vs 2st
t(596.20) = -10.82, p = 0.000, Cohen d = 1.38, 95% CI (-4.66 to -3.23)
1st vs 3rd
t(597.96) = -12.76, p = 0.000, Cohen d = 1.65, 95% CI (-5.44 to -3.99)
dbas_expectation
1st vs 2st
t(577.77) = -7.96, p = 0.000, Cohen d = 1.03, 95% CI (-1.98 to -1.20)
1st vs 3rd
t(578.71) = -10.14, p = 0.000, Cohen d = 1.33, 95% CI (-2.45 to -1.66)
dbas_medication
1st vs 2st
t(577.75) = -1.59, p = 0.223, Cohen d = 0.21, 95% CI (-0.66 to 0.07)
1st vs 3rd
t(578.69) = -2.91, p = 0.008, Cohen d = 0.38, 95% CI (-0.92 to -0.18)
psas_somatic
1st vs 2st
t(564.54) = -3.01, p = 0.005, Cohen d = 0.39, 95% CI (-0.27 to -0.06)
1st vs 3rd
t(565.09) = -4.24, p = 0.000, Cohen d = 0.56, 95% CI (-0.34 to -0.12)
psas_cognitive
1st vs 2st
t(575.27) = -8.80, p = 0.000, Cohen d = 1.14, 95% CI (-0.78 to -0.50)
1st vs 3rd
t(576.12) = -10.47, p = 0.000, Cohen d = 1.38, 95% CI (-0.91 to -0.63)
psqi_global
1st vs 2st
t(588.25) = -10.87, p = 0.000, Cohen d = 1.40, 95% CI (-3.75 to -2.60)
1st vs 3rd
t(589.60) = -12.70, p = 0.000, Cohen d = 1.66, 95% CI (-4.34 to -3.18)
mic_attention
1st vs 2st
t(571.43) = -4.27, p = 0.000, Cohen d = 0.55, 95% CI (-0.39 to -0.15)
1st vs 3rd
t(572.17) = -5.52, p = 0.000, Cohen d = 0.73, 95% CI (-0.48 to -0.23)
mic_executive
1st vs 2st
t(564.96) = -3.11, p = 0.004, Cohen d = 0.41, 95% CI (-0.31 to -0.07)
1st vs 3rd
t(565.52) = -5.09, p = 0.000, Cohen d = 0.67, 95% CI (-0.44 to -0.20)
mic_memory
1st vs 2st
t(558.80) = -4.18, p = 0.000, Cohen d = 0.55, 95% CI (-0.36 to -0.13)
1st vs 3rd
t(559.21) = -4.78, p = 0.000, Cohen d = 0.63, 95% CI (-0.40 to -0.17)
nb_pcs
1st vs 2st
t(559.27) = 2.80, p = 0.011, Cohen d = -0.37, 95% CI (0.56 to 3.21)
1st vs 3rd
t(559.70) = 3.53, p = 0.001, Cohen d = -0.47, 95% CI (1.07 to 3.76)
nb_mcs
1st vs 2st
t(568.48) = 6.61, p = 0.000, Cohen d = -0.86, 95% CI (3.92 to 7.23)
1st vs 3rd
t(569.13) = 8.10, p = 0.000, Cohen d = -1.07, 95% CI (5.25 to 8.61)
Within control group
isi
1st vs 2st
t(541.68) = -7.61, p = 0.000, Cohen d = 0.86, 95% CI (-3.09 to -1.82)
1st vs 3rd
t(548.03) = -8.56, p = 0.000, Cohen d = 1.00, 95% CI (-3.50 to -2.19)
who
1st vs 2st
t(529.52) = 2.44, p = 0.030, Cohen d = -0.28, 95% CI (0.14 to 1.32)
1st vs 3rd
t(533.45) = 2.98, p = 0.006, Cohen d = -0.35, 95% CI (0.31 to 1.53)
phq
1st vs 2st
t(522.50) = -2.34, p = 0.040, Cohen d = 0.27, 95% CI (-1.43 to -0.12)
1st vs 3rd
t(525.31) = -1.84, p = 0.132, Cohen d = 0.22, 95% CI (-1.31 to 0.04)
gad
1st vs 2st
t(523.43) = -1.29, p = 0.396, Cohen d = 0.15, 95% CI (-1.11 to 0.23)
1st vs 3rd
t(526.38) = -1.69, p = 0.183, Cohen d = 0.20, 95% CI (-1.29 to 0.10)
wsas
1st vs 2st
t(525.88) = -1.18, p = 0.479, Cohen d = 0.13, 95% CI (-2.19 to 0.55)
1st vs 3rd
t(529.20) = -0.12, p = 1.000, Cohen d = 0.01, 95% CI (-1.50 to 1.32)
shps_arousal
1st vs 2st
t(536.49) = -3.30, p = 0.002, Cohen d = 0.38, 95% CI (-0.31 to -0.08)
1st vs 3rd
t(541.73) = -3.58, p = 0.001, Cohen d = 0.42, 95% CI (-0.34 to -0.10)
shps_schedule
1st vs 2st
t(523.93) = -1.68, p = 0.188, Cohen d = 0.19, 95% CI (-0.22 to 0.02)
1st vs 3rd
t(526.95) = -2.14, p = 0.066, Cohen d = 0.25, 95% CI (-0.25 to -0.01)
shps_behavior
1st vs 2st
t(530.68) = 0.48, p = 1.000, Cohen d = -0.06, 95% CI (-0.08 to 0.12)
1st vs 3rd
t(534.81) = 0.18, p = 1.000, Cohen d = -0.02, 95% CI (-0.09 to 0.11)
shps_environment
1st vs 2st
t(530.14) = -0.97, p = 0.662, Cohen d = 0.11, 95% CI (-0.18 to 0.06)
1st vs 3rd
t(534.17) = -0.99, p = 0.646, Cohen d = 0.12, 95% CI (-0.18 to 0.06)
dbas_consequence
1st vs 2st
t(531.17) = -2.39, p = 0.034, Cohen d = 0.27, 95% CI (-0.61 to -0.06)
1st vs 3rd
t(535.38) = -4.61, p = 0.000, Cohen d = 0.54, 95% CI (-0.95 to -0.38)
dbas_worry
1st vs 2st
t(542.50) = -3.81, p = 0.000, Cohen d = 0.43, 95% CI (-1.87 to -0.60)
1st vs 3rd
t(549.04) = -5.54, p = 0.000, Cohen d = 0.65, 95% CI (-2.50 to -1.19)
dbas_expectation
1st vs 2st
t(532.71) = -1.95, p = 0.104, Cohen d = 0.22, 95% CI (-0.69 to 0.00)
1st vs 3rd
t(537.21) = -4.26, p = 0.000, Cohen d = 0.50, 95% CI (-1.13 to -0.42)
dbas_medication
1st vs 2st
t(532.70) = 2.23, p = 0.053, Cohen d = -0.25, 95% CI (0.04 to 0.69)
1st vs 3rd
t(537.20) = 1.83, p = 0.137, Cohen d = -0.21, 95% CI (-0.02 to 0.64)
psas_somatic
1st vs 2st
t(526.16) = 3.03, p = 0.005, Cohen d = -0.35, 95% CI (0.05 to 0.24)
1st vs 3rd
t(529.53) = 0.12, p = 1.000, Cohen d = -0.01, 95% CI (-0.09 to 0.10)
psas_cognitive
1st vs 2st
t(531.45) = -3.20, p = 0.003, Cohen d = 0.37, 95% CI (-0.33 to -0.08)
1st vs 3rd
t(535.71) = -5.52, p = 0.000, Cohen d = 0.65, 95% CI (-0.49 to -0.23)
psqi_global
1st vs 2st
t(538.16) = -5.09, p = 0.000, Cohen d = 0.58, 95% CI (-1.82 to -0.81)
1st vs 3rd
t(543.73) = -4.95, p = 0.000, Cohen d = 0.58, 95% CI (-1.84 to -0.79)
mic_attention
1st vs 2st
t(529.53) = -0.39, p = 1.000, Cohen d = 0.04, 95% CI (-0.13 to 0.09)
1st vs 3rd
t(533.46) = 0.59, p = 1.000, Cohen d = -0.07, 95% CI (-0.08 to 0.15)
mic_executive
1st vs 2st
t(526.36) = -0.62, p = 1.000, Cohen d = 0.07, 95% CI (-0.14 to 0.07)
1st vs 3rd
t(529.76) = -0.90, p = 0.738, Cohen d = 0.11, 95% CI (-0.16 to 0.06)
mic_memory
1st vs 2st
t(523.40) = 0.62, p = 1.000, Cohen d = -0.07, 95% CI (-0.07 to 0.13)
1st vs 3rd
t(526.34) = -1.23, p = 0.435, Cohen d = 0.15, 95% CI (-0.17 to 0.04)
nb_pcs
1st vs 2st
t(523.62) = -1.47, p = 0.282, Cohen d = 0.17, 95% CI (-2.03 to 0.29)
1st vs 3rd
t(526.60) = -1.30, p = 0.389, Cohen d = 0.15, 95% CI (-1.99 to 0.41)
nb_mcs
1st vs 2st
t(528.08) = 2.71, p = 0.014, Cohen d = -0.31, 95% CI (0.55 to 3.46)
1st vs 3rd
t(531.76) = 2.96, p = 0.006, Cohen d = -0.35, 95% CI (0.76 to 3.76)
Plot
Clinical significance
| T1 | T2 | T3 | ||||||
outcome | control1 | treatment1 | p-value2 | control1 | treatment1 | p-value2 | control1 | treatment1 | p-value2 |
isi | 89% | 85% | 0.206 | 61% | 31% | 0.000 | 56% | 29% | 0.000 |
psqi | 96% | 97% | 0.586 | 89% | 74% | 0.003 | 89% | 65% | 0.000 |
phq | 31% | 38% | 0.148 | 32% | 19% | 0.019 | 30% | 18% | 0.032 |
gad | 30% | 33% | 0.494 | 26% | 17% | 0.061 | 27% | 16% | 0.042 |
wsas | 74% | 72% | 0.721 | 68% | 55% | 0.041 | 70% | 49% | 0.001 |
1% | |||||||||
2Pearson's Chi-squared test | |||||||||